Numbers, when used wisely, drive better UX design
How analytics empower UX designers to kill biases and make data-driven decisions
Spending countless hours doing extensive user research, evaluation, and drafting ‘how might we’ statements yet often stuck at convincing stakeholders of the rightness of insights and suggested improvements — is a challenge many of us have faced. Imagine if we had a power that helped us defend our proposals. That power is UX analytics.
I have been working towards transforming an existing website’s experience journey for a client. Kick-started by digging deep into the analytics data collected over a long period uncovered some unexpected findings about user behavior. It is by working on this project that I was introduced to the domain of analytics and it has ever since changed the way I approach a design problem.
When walking in the user’s shoes, designers sometimes forget to take off their own.
With increasing experience in the design field, we constantly absorb information and form our perspectives. All the profound knowledge is invaluable in crafting relevant and meaningful design solutions for users. But the more we learn, the easier it is to assume we know what users need and it often becomes challenging to remain completely unbiased in our approach. Even the most seasoned designers aren’t immune to the subtle trap of design biases.
Data as Your Design Ally
Referring to analytics data early in the research phase is an efficient way of eluding design biases that may occur based on the way information is presented and our preconceived notions.
With tracking cookies integrated into websites, it becomes possible to collect and monitor every small interaction of the users like clicks, hovers, user journeys, pages viewed, time spent, etc, and over time it sums up to a large amount of data. This behavioral data offers a preliminary understanding of the website’s performance and experience gaps.
Analytics gives designers the ability to verify intuitions and turn them into impact.
What is UX analytics?
UX analytics refers to deducing actionable insights from the massive amounts of user behavioral data collected and stored over time. These insights aid decision-making during different touchpoints across the design process.
When to use analytics?
Primarily, analytics can be utilized only when you wish to improve an existing web application either entirely or just a few sections of it.
The user-centered design process must start with the evaluation of existing experience through analytics platforms.
These platforms collect data of large sample sizes that could exceed thousands or millions of website visitors. Hence, it is good practice to kick off the redesign task by looking at the big picture, marking the areas of interest, and then drilling down to specific issues. This early analysis sets the stage for further study.
But why should designers bother about analytics when we have data experts?
Learning about analytics may seem challenging at first. Being a UX designer myself, I felt overwhelmed even at the thought of diving into this subject of numbers, statistics, graphs, and analytics platforms. I was progressing to absorb more about what seemed complex, only to realize how much of an immense value it adds to a designer’s skill set and the solutions we deliver.
I always wondered if I needed to spend time learning analytics when I could seek support from data experts within the project team. As I collaborated with cross-functional teams, it became clearer to me that as UX designers we can rationalize the data better when coupled with an understanding of users and project goals.
Undoubtedly, the data experts are proficient in the technical aspects of how numbers are derived and what they mean. But with a deeper understanding of the user personas, their pain points and behaviors, a designer can filter relevant data and deduce logical actionable insights, especially the ones that cater to the user’s needs. This aids designers in looking beyond numbers and allows them to interpret the data in a way that is more meaningful for the experience and the business.
To leverage the data, it is not necessary to thoroughly learn the analytics platforms. One can always start small by learning basic terms and concepts to help you communicate with a data expert and request a report that adheres to your requirements.
How does data add value?
- Informed decisions-:
Incorporating analytics into your research offers ahead-of-time clarity on existing issues and builds a dependable foundation, guiding your direction and fortifying your decisions.
More and more businesses have started to realize the value of data and prefer facts over intuitions. When the design proposals are backed by data, it becomes easy to convey the relevance of your suggestions to the stakeholders and reduce the potential pushback from those who might view qualitative findings as subjective.
As William Hudson rightly said, “Analytics are easier to sell than qualitative methods”.
2. Strategize project goals:
Analytics platforms offer performance metrics that give a high-level overview of the entire site. Revealing which page or page groups are receiving good engagement from users and which need attention, helps to determine the order in which issues should be addressed. Based on the level of severity, the problem areas can be prioritized for further research and improvement.
3. Builds a foundation for qualitative analysis:
Relying just on the data is never enough. While quantitative data helps you understand what issues users are facing and their level of severity, qualitative research delves into identifying why a certain issue could be occurring.
For example-
Data can be used to identify the percentage of users not engaging with a particular page and that they drop off from the website after viewing it. With heat-maps, you can also analyze and mark which zones receive the least interaction. These observations can be used as a criterion to conduct usability testing and realize why they are not engaging with identified zones.
Insights from quantitative data builds a foundation for qualitative analysis.
4. Identify shortfalls:
There are times when despite all the research and well-designed pages, the users still miss the target and may not interact in a certain way. Such insights can be deduced in a breeze since the data is readily available through analytic platforms and does not require any setup for the after-go-live testing. It allows us to make quick fixes and fill the experience gaps.
5. Impact Analysis:
With many years of user interaction data stored as graphs, charts, and tables it enables us to visualize growth patterns and setbacks.
After the new solution is implemented, outcome assessment becomes possible by comparing the before and after results. Performance shifts over a period can be analyzed to measure the ROI and effectiveness of the design solution.
Takeaways
Designers lean towards creativity and visuals rather than numbers. However, it is crucial to increase expertise around UX analytics and include it in the design process to stay relevant in the field where data-informed decisions hold great value.
Through analytics, the effectiveness of an experience can be measured. It acts as an enabler to prioritize improvements based on severity of inconsistencies in the current system, define its ROI, and ultimately provide a roadmap for the CX strategy.
Great experiences aren’t just intuitive; they are informed.
References:
- “Data Analysis: Techniques, Tools, and Processes” by The Interaction Design Foundation.
- “Learn Data Analytics in 2024 for Better UX Design” by Mizko on Youtube.
- “UX Analytics 101: How to Use Data to Improve User Experiences” by Amplitude
